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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30304?offset=780</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35292/pgap-x-extension-on-pan-genome-analysis-pipeline</guid>
	<pubDate>Tue, 23 Jan 2018 11:41:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35292/pgap-x-extension-on-pan-genome-analysis-pipeline</link>
	<title><![CDATA[PGAP-X: Extension on pan-genome analysis pipeline]]></title>
	<description><![CDATA[<p>PGAP-X is a microbial comparative genomic analysis platform with graphic interface. Serials of algorithms and methodologies have been developed and integrated to analyze and visualize genomics structure variation, gene distribution with different conservative levels, and genetic variation from pan-genome sight. At the same time, analytical result data from many other programs, including genome alignment result and orthologs clusters, are also supported to be further analyzed or visualized in PGAP-X. The workflow and feature snapshot in PGAP-X were shown as Fig.1 and Fig.2.</p>
<div><img src="https://pgapx.ybzhao.com/image/f1.jpg" alt="image" style="border: 0px; border: 0px;"></div>
<div>&nbsp;</div>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://pgapx.ybzhao.com/" rel="nofollow">https://pgapx.ybzhao.com/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36730/bprna-large-scale-automated-annotation-and-analysis-of-rna-secondary-structure</guid>
	<pubDate>Wed, 23 May 2018 03:24:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36730/bprna-large-scale-automated-annotation-and-analysis-of-rna-secondary-structure</link>
	<title><![CDATA[bpRNA: large-scale automated annotation and analysis of RNA secondary structure]]></title>
	<description><![CDATA[<p>bpRNA, a novel annotation tool capable of parsing RNA structures, including complex pseudoknot-containing RNAs, to yield an objective, precise, compact, unambiguous, easily-interpretable description of all loops, stems, and pseudoknots, along with the positions, sequence, and flanking base pairs of each such structural feature.</p>
<p>The bpRNA code is written in perl and requires the Graph perl module. Several additional scripts for analysis are included. The source code is available at http://github.com/hendrixlab/bpRNA.</p><p>Address of the bookmark: <a href="http://github.com/hendrixlab/bpRNA" rel="nofollow">http://github.com/hendrixlab/bpRNA</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42165/bioinformatics-scientistresearch-software-engineer-at-university-of-dundee-dundee-united-kingdom</guid>
  <pubDate>Wed, 26 Aug 2020 10:31:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Scientist/Research Software Engineer at University of Dundee Dundee, United Kingdom]]></title>
  <description><![CDATA[
<p>We are recruiting for an exceptional individual to join us as a computational scientist, bioinformatician, or (research) software engineer with an interest in interactive data analysis platforms for biology and medicine within our Jalview (www.jalview.org) research software engineering team.</p>

<p>More at https://www.jobs.dundee.ac.uk/fe/tpl_uod01.asp?s=4A515F4E5A565B1A&amp;jobid=104342,2382988671&amp;key=147934117&amp;c=99413415238921&amp;pagestamp=sesxbbuyifokdsfygf</p>

<p>Last date: 30th August 2020</p>

<p>Informal enquiries about this position may be made to Prof. Geoff Barton (gjbarton@dundee.ac.uk) or Dr Jim Procter (jprocter@dundee.ac.uk). To find out more about Jalview research software engineering team please visit www.jalview.org and www.compbio.dundee.ac.uk</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40298/environment-for-tree-exploration-ete-is-a-python-programming-toolkit-that-assists-in-the-recontruction-manipulation-analysis-and-visualization-of-phylogenetic-trees</guid>
	<pubDate>Wed, 27 Nov 2019 05:32:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40298/environment-for-tree-exploration-ete-is-a-python-programming-toolkit-that-assists-in-the-recontruction-manipulation-analysis-and-visualization-of-phylogenetic-trees</link>
	<title><![CDATA[Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees]]></title>
	<description><![CDATA[<p><span>The Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees (although clustering trees or any other tree-like data structure are also supported).</span></p>
<p><span>Other tools</span></p>
<p><span><a href="https://github.com/shenwei356/taxonkit">https://github.com/shenwei356/taxonkit</a></span></p>
<p>&nbsp;</p>
<ul>
<li>ETE, version:&nbsp;<a href="https://pypi.org/project/ete3/3.1.1/">3.1.1</a></li>
<li>BioPython, version:&nbsp;<a href="https://pypi.org/project/biopython/1.73/">1.73</a></li>
<li>taxadb, version:&nbsp;<a href="https://pypi.org/project/taxadb/0.9.0">0.10.1</a></li>
<li>TaxonKit, version:&nbsp;<a href="https://github.com/shenwei356/taxonkit/releases/tag/0.10.1">0.5.0</a></li>
</ul><p>Address of the bookmark: <a href="https://pypi.org/project/ete3/3.1.1/" rel="nofollow">https://pypi.org/project/ete3/3.1.1/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42227/two-faculty-positions-at-national-taiwan-university-taipei-taiwan</guid>
  <pubDate>Thu, 22 Oct 2020 04:53:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[Two Faculty Positions at National Taiwan University, Taipei, Taiwan]]></title>
  <description><![CDATA[
<p>The Department of Agronomy at National Taiwan University, Taipei, Taiwan,<br />invites applications for two full-time faculty positions beginning August<br />1, 2021 at the rank of Assistant Professor, Associate Professor or<br />Professor in Biometry and Bioinformatics and Plant Breeding and Genetics,<br />respectively.</p>

<p>A qualified candidate should hold a Ph.D. in a relevant field including<br />Agronomy, Statistics, Bioinformatics, Plant Breeding, Plant Genetics or<br />Quantitative Genetics. For the position in Biometry and Bioinformatics, the<br />applicants capable of teaching fundamental statistics/bioinformatics<br />courses or with experience in crop science are preferable; for Plant<br />Breeding and Genetics, the applicants capable of teaching fundamental plant<br />breeding courses, with experience in crop breeding, or training in<br />quantitative genetics are preferred.</p>

<p>The application package should include two letters of reference and five<br />printed copies of the following documents (1) curriculum vitae, (2)<br />publication list, (3) undergraduate and graduate transcripts if applying<br />for the Assistant Professorship, (4) a photocopy of the Ph.D. diploma, (5)<br />teaching plan and course outline or syllabus (6) research proposal, (7) a<br />cover letter indicating the rank to apply, and one representative original<br />research article which was published by the applicant being the 1st or<br />corresponding author in an SCI peer-reviewed journal within 5 years (after<br />August 1, 2016); a copy of doctoral dissertation can be the representative<br />article if applying for the Assistant Professorship; (8) reprints of the<br />selected publications published within 7 years (after August 1, 2014).</p>

<p>The application package should mail to the Chair, Dr. Li-yu Daisy Liu<br />(lyliu@ntu.edu.tw), in the Department of Agronomy, National Taiwan<br />University, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan, before<br />December 15, 2020 for full consideration.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41006/netgo-r-shiny-package-for-network-integrated-pathway-enrichment-analysis</guid>
	<pubDate>Wed, 12 Feb 2020 12:40:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41006/netgo-r-shiny-package-for-network-integrated-pathway-enrichment-analysis</link>
	<title><![CDATA[netGO: R-Shiny package for network-integrated pathway enrichment analysis]]></title>
	<description><![CDATA[<p>netGO is an R/Shiny package for network-integrated pathway enrichment analysis.<br>netGO provides user-interactive visualization of enrichment analysis results and related networks.</p>
<p>Currently, netGO supports analysis for four species (<em><a href="https://github.com/unistbig/netGO-Data/tree/master/Human">Human</a>,&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Mouse">Mouse</a>,&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Arabidopsis">Arabidopsis thaliana</a>,and&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Yeast">Yeast</a></em>)<br>These data are available from&nbsp;<a href="https://github.com/unistbig/netGO-Data">netGO-Data</a>&nbsp;repository.</p>
<p><a href="https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa077/5728635">https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa077/5728635</a></p><p>Address of the bookmark: <a href="https://github.com/unistbig/netGO" rel="nofollow">https://github.com/unistbig/netGO</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42672/introduction-to-bioinformatics-and-computational-biology</guid>
	<pubDate>Mon, 25 Jan 2021 01:32:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42672/introduction-to-bioinformatics-and-computational-biology</link>
	<title><![CDATA[Introduction to Bioinformatics and Computational Biology]]></title>
	<description><![CDATA[<p><span>This is the course material for STAT115/215 BIO/BST282 at Harvard University.</span></p>
<p>Xiaole Shirley Liu (lead instructor)<br>Joshua Starmer<br>Martin Hemberg<br>Ting Wang<br>Feng Yue</p>
<p>Ming Tang<br>Yang Liu<br>Jack Kang<br>Scarlett Ge<br>Jiazhen Rong<br>Phillip Nicol<br>Maartin De Vries</p>
<p>We thank many colleagues in the community, who helped Dr.&nbsp;Liu in prepare the STAT115/215 BIO/BST282 course over the years.&nbsp;</p><p>Address of the bookmark: <a href="https://liulab-dfci.github.io/bioinfo-combio/" rel="nofollow">https://liulab-dfci.github.io/bioinfo-combio/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42568/breedbase-is-a-comprehensive-breeding-management-and-analysis-software</guid>
	<pubDate>Wed, 06 Jan 2021 19:45:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42568/breedbase-is-a-comprehensive-breeding-management-and-analysis-software</link>
	<title><![CDATA[Breedbase is a comprehensive breeding management and analysis software]]></title>
	<description><![CDATA[<p><span>Breedbase is a comprehensive breeding management and analysis software. It can be used to design field layouts, collect phenotypic information using tablets, support the collection of genotyping samples in a field, store large amounts of high density genotypic information, and provide Genomic Selection related analyses and predictions. Breedbase supports the BrAPI standard.</span></p><p>Address of the bookmark: <a href="https://breedbase.org/" rel="nofollow">https://breedbase.org/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42809/bioinformatics-in-africa-part2-kenya</guid>
	<pubDate>Sat, 06 Feb 2021 13:23:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42809/bioinformatics-in-africa-part2-kenya</link>
	<title><![CDATA[Bioinformatics in Africa: Part2 - Kenya]]></title>
	<description><![CDATA[<p>International Livestock Research Institute (ILRI):</p><p>Under&nbsp; &nbsp;a&nbsp; &nbsp;NEPAD&nbsp; &nbsp;initiative,&nbsp; &nbsp;the&nbsp; &nbsp;Biosciences&nbsp; &nbsp;Eastern&nbsp; &nbsp;and&nbsp; &nbsp;Central&nbsp; &nbsp;Africa&nbsp; &nbsp;(BECA)&nbsp; (www.biosciencesafrica.org) was established at ILRI. BECA consists of a hub, regional nodes, and&nbsp; other affiliated laboratories and partner institutes. A state of the art joint Bioinformatics Platform&nbsp; (www.becabioinfo.org), whose overall goal is to provide a coherent and powerful bioinformatics&nbsp; infrastructure for use by all scientists in East and central Africa. The Platform goal requires both&nbsp; physical and intellectual developments that together provide researchers with access to diverse&nbsp; infrastructure in a wide&shy;area network, thereby addressing four important aspects of bioinformatics:&nbsp;</p><p>1) Science: bioinformatics tools for data integration and visualization, standardization of data&nbsp; formats and data analysis strategies, and distribution of analysis tasks over local&shy; and widearea networks are in development;&nbsp;</p><p>2)&nbsp; Bioinformatics Support Facility: provides assistance and custom programming to projects&nbsp; and those unable to establish a bioinformatics support function intrinsic to their project due&nbsp; to shortage of qualified personnel or lack of funding;&nbsp;</p><p>3) Hardware Platform: provide a powerful high performance computing platform capable of&nbsp; handling the largest analysis needs for projects;&nbsp;</p><p>4) Bioinformatics Training for East and central African scientists: While many Web&shy;based&nbsp; tools are available to the wet&shy;lab researcher, the Web is not well suited for tasks beyond&nbsp; single&shy;sequence annotation. Researchers need to become productive in a server&shy;based Unix&nbsp; environment with its wealth of scripting and automation tools. Even at an entry&shy;level, this&nbsp; can be an intimidating task if proper guidance is not available.</p><p>International&nbsp;Centre&nbsp;of&nbsp;Insect&nbsp;Physiology&nbsp;and&nbsp;Ecology&nbsp;(ICIPE): ICIPE&rsquo;s&nbsp;research&nbsp;focus&nbsp;is&nbsp;on&nbsp;insect&nbsp;biology,&nbsp;in&nbsp;order&nbsp;to&nbsp;improve&nbsp;the&nbsp;wellbeing&nbsp;of&nbsp;the&nbsp;peoples&nbsp;of&nbsp;the&nbsp; tropics&nbsp;through&nbsp;insect&nbsp;science.&nbsp;There&nbsp;is&nbsp;a&nbsp;commitment&nbsp;to&nbsp;utilise&nbsp;contemporary&nbsp;science&nbsp;in&nbsp;order&nbsp;to&nbsp; limit&nbsp;the&nbsp;impact&nbsp;of&nbsp;disease&nbsp;vectors,&nbsp;and&nbsp;agricultural&nbsp;pests.&nbsp;The&nbsp;understanding&nbsp;of&nbsp;the&nbsp;mechanisms&nbsp; associated&nbsp;with&nbsp;behaviour&nbsp;(e.g.&nbsp;attraction&nbsp;and&nbsp;repellency)&nbsp;is&nbsp;crucial.&nbsp;ICIPE&nbsp;seeks&nbsp;to&nbsp;enhance&nbsp;its&nbsp; bioinformatics&nbsp;capacity&nbsp;in&nbsp;order&nbsp;to&nbsp;support&nbsp;data&nbsp;from&nbsp;various&nbsp;EST&nbsp;projects&nbsp;designed&nbsp;to&nbsp;gain&nbsp;insights&nbsp; into&nbsp;the&nbsp;insect&nbsp;ecology&nbsp;and&nbsp;plant&nbsp;pathogen&nbsp;interactions&nbsp;though&nbsp;studies&nbsp;of&nbsp;metabolic&nbsp;pathways&nbsp; associated&nbsp;with&nbsp;production&nbsp;of&nbsp;all&nbsp;elochemicals.&nbsp;</p><p>Long&shy;term training activities:</p><p>Kenyatta University: An introductory course in Bioinformatics is offers to MSc Biotechnology&nbsp; students. This comprises of 35 hours of lectures and practicals.</p><p>University of Nairobi: A centre for Biotechnology and Bioinformatics (CEBIB), which will offer&nbsp; postgraduate training (diplomas, MSc and PhD) in areas of biotechnology and bioinformatics has&nbsp; recently been launched. Other universities in Kenya, including Egerton, Maseno and the Jomo Kenyatta University of&nbsp; Agriculture and Technology offer introductory courses to undergraduates in biomedical sciences. In addition, under the BECA platform MSc and PhD fellowships are being made available for&nbsp; Bioinformatics students. ILRI is forging links with Universities in South Africa and the United&nbsp; Kingdom to provide access to courses and training material.&nbsp;</p><p>Research Interest and Activities:</p><p>The following are the present areas of research interest: 1. EST clustering 2. Genome sequencing and annotation 3. Functional genomics and proteomics (including key tropical pathogens) 4. Structural bioinformatics 5. Development of Bioinformatics Data Management Systems 6. Gene Mining 7. High Throughput Genotyping 8. Microarray data management and analysis 9. Metagenomics 10. Immunoinformatics 11. Host&shy;pathogen interaction 12. High performance computing and grid development 13. Parasite transfection technologies 14. Cell cycle regulation 15. Population genetics 16. Vector genomics 17. Drug, vaccine and diagnostic target discovery</p><p>More at&nbsp;Web&nbsp;site&nbsp;and&nbsp;links:</p><p>http://www.ilri.cgiar.org/</p><p>http://www.icipe.org/ &nbsp; &nbsp;</p><p>http://www.uonbi.ac.ke/cebib</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43815/kebabs-package-provides-functionality-for-kernel-based-analysis-of-biological-sequences-via-support-vector-machine-svm-based-methods</guid>
	<pubDate>Fri, 04 Mar 2022 00:14:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43815/kebabs-package-provides-functionality-for-kernel-based-analysis-of-biological-sequences-via-support-vector-machine-svm-based-methods</link>
	<title><![CDATA[kebabs: package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods]]></title>
	<description><![CDATA[<p><span>The&nbsp;</span><tt>kebabs</tt><span>&nbsp;package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods. Biological sequences include DNA, RNA, and amino acid (AA) sequences. Sequence kernels define similarity measures between sequences. The package implements some of the most important kernels for sequence analysis in a very flexible and efficient way and extends the standard position-independent functionality of these kernels in a novel way to take the position of patterns in the sequences into account for the similarity measure.</span></p>
<p>http://www.bioinf.jku.at/software/kebabs/</p>
<p>http://bioconductor.org/packages/release/bioc/vignettes/kebabs/inst/doc/kebabs.pdf</p><p>Address of the bookmark: <a href="http://www.bioinf.jku.at/software/kebabs/" rel="nofollow">http://www.bioinf.jku.at/software/kebabs/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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